Nausea, which is a noxious symptom that often leads to vomiting, is a problem frequently encountered in the field of medicine. Patients recovering from anesthesia, and those undergoing chemotherapy for cancer, for example, frequently become gravely nauseous.
Nausea can have serious implications aside from the extreme discomfort experienced by a patient or other individual who experiences it. In particular, nausea can be dangerous because the associated retching creates high pressures within the body that may cause hemorrhaging and disruption of sutures, especially in the eye and brain. In addition, vomiting can cause excessive loss of electrolytes as well as the possibility of aspiration in patients who are recovering from surgery or who are otherwise incapacitated.
It would thus be most useful in the field of medicine if a simple automated arrangement were available which reliably and timely predicts the onset of nausea. An objective physiological measure of impending nausea would be useful in managing patients with a wide variety of medical and surgical procedures. However, known prior art nausea detection techniques require constant observation and monitoring of the patient by a skilled individual.
Research has shown that gastric dysrhythmia (abnormal stomach electrical activity) heralds the onset of nausea induced during motion sickness and by the administration of the narcotic drug morphine sulfate. Gastric dysrhythmias are abnormal gastric myoelectrical rhythms termed tachygastrias (3.6-9.9 cycles per minute (cpm)) and bradygastrias (0-2.4 cpm) and are differentiated from normal gastric myoelectrical rhythms which occur within the range of 2.4 to 3.6 cpm.
Electrogastrograpy is a non-invasive method for recording gastric myoelectrical activity or electrogastrograms (EGGs) from normal rhythms to gastric dysrhythmias. Gastric dysrhythmias have been recorded with this method in patients with nausea of pregnancy, diabetic and idiopathic gastroparesis, and in patients with idiopathic nausea and drug-induced nausea. The onset of gastric dysrhythmias precedes the report of nausea by 1-20 minutes, depending on specific circumstances. The ability to recognize these gastric dysrhythmias automatically, in real time, would greatly improve the treatment of nausea at early stages and afford the physician an opportunity to prevent severe nausea, retching and vomiting.
The onset of gastric dysrhythmias and the loss of normal 2.4-3.6 cpm gastric rhythm may be identified by visual inspection of hard copy EGG records by a trained and specialized clinician or researcher who is skilled in the interpretation of gastric myoelectrical activity. Thus, known prior art devices are only able to record raw physiological EGG data and display it in real time, or provide spectral analyses off-line.
Real-time computer analysis, on the other hand, offers on-line quantitative analysis of gastric dysrhythmias. Thus, on-line reproduction of the gastric dysrhythmias and on-line quantitative and spectral analysis of the EGG signal would be important advances in the diagnosis and treatment of nausea.
Previous efforts to develop such a device, however, have been complicated by the fact that the electrical signals associated with stomach activity, and which are sensed for the purpose of analyzing gastric dysrhythmias, have a frequency which is extremely low, being on the order of a few cycles per minute (approximately 0.0-0.25 Hz) Thus far, efforts to develop an automated arrangement for analyzing electrical signals associated with stomach myoelectrical patterns have failed, due largely to the inability to eliminate artifacts (spurious signal components) in the signals. (That is, the signal to noise ratio is very low.) The existence of such artifacts has heretofore rendered any form of computer analysis unreliable.